The long-term objective of this project is to improve human health and impact health care delivery by developing intelligent technologies that aid with health monitoring and intervention. Our immediate objective is to design, evaluate and validate machine learning-based software algorithms that recognize daily activities, provide activity-aware medicine reminder interventions and provide insights on intervention timings that yield successful compliance. We hypothesize that many individuals with needs for medicine intervention can be more compliant with their medicine regimen if prompts are provided at the right times and in the right context. We plan to accomplish these objectives by 1) enhancing and validating software algorithms that recognize daily activities and activity transitions, 2) developing and validating activity-aware medicine prompting interventions for mobile devices, and 3) designing technologies to analyze medicine reminder successes and failures. We are well positioned to significantly advance the clinical translation of mobile device-based medicine reminders for use by heart failure patients. The proposed work represents a natural extension of our prior research and is innovative because it will partner real-time methodologies for validation and algorithmic development with smart phone data, utilize novel activity discovery algorithms, and employ activity recognition and prediction algorithms in the development of activity-aware prompting.